A battery state of charge is routinely displayed to the user for numerous types of products. There are many examples of inaccuracies causing incorrect displaying of the state of charge. For example, with Nickel Metal Hydride (NiMH) batteries, it is difficult to predict their state of charge (SOC) because of the charging and discharging characteristics of NiMH battery technology. It can be shown on charge and discharge curves that while voltages can be the same, the SOC can be substantially different. Thus, it is very difficult to use an open circuit voltage to accurately predict the SOC of the NiMH battery, as the battery operating mode (charging, discharging, or charge sustaining) should be known. Other battery technologies have similar issues creating a difficult environment for accurately estimating the state of charge for any particular battery technology. There fails to exist an accurate means of estimating the state of charge without necessarily increasing the cost of an overall system.
In some SOC measuring schemes, a sense resistor is used to measure the current flowing into or out of a battery. The sense resistor value depends on the currents being measured. In general, a sense resistor should be selected so that the voltage drop across that resistor exceeds a predetermined voltage for the lowest current representing the majority of the battery drain, and the lowest practical voltage drop across the sense resistor is achieved to maximize the useful voltage available from the battery pack.
U.S. Pat. No. 6,359,419 by Verbrugge et. al. discusses a method of determining a state of charge of a battery by determining a “current-based” state of charge measurement based on coulomb integration, determining a voltage-based state of charge measurement based on the resistance of the battery and a hysteresis voltage, and combining the current-based state of charge measurement and the voltage-based state of charge measurement with a weighting factor to generate the state of charge of the battery. Even if such a system were accurate, it appears to be quite computatively complex and expensive. Furthermore, such a system may not work well for an induction charging system where there is no physical connection between the battery and the charging apparatus or device.
Induction charging systems are well known in the field of portable electrical devices. For example, portable motorized toothbrushes typically contain a rechargeable battery which is charged by induction. Similarly, portable wireless communication devices, such as two-way radio frequency (RF) radios, cellular phones, paging devices, and wireless communicators, commonly utilize a rechargeable battery that, in certain applications, is recharged by contactless induction charging. Such portable devices are becoming increasingly popular because of the convenience afforded a user by working without a wired connection, such as not having to connect plugs to sockets, not having to precisely locate and plug a unit to be charged, and the ability to quickly remove from a charger unit a device that has been recharged (“grab-n-go”).
Unfortunately, present induction charging systems either have little control over input voltage to the charge control circuitry, or such systems employ wireless techniques to control these parameters by regulating the base of the charging system. Notably, implementation of wireless control techniques within the charging system is expensive. Accurately estimating the SOC of a battery being charged and utilizing such information would allow for a more efficient charging system.